Applied Workflows in Geodise e-Science Workflow Services Workshop Edinburgh (Dec 3 rd – 5 th 2003) Dec 4 th 2003 Prof Simon Cox Computational Engineering.

Applied Workflows in Geodise e-Science Workflow Services Workshop Edinburgh (Dec 3 rd – 5 th 2003) Dec 4 th 2003 Prof Simon Cox Computational Engineering & Design Group School of Engineering Sciences University of Southampton

© Geodise Project, 2001-2004. http://www.geodise.org/ Grid Enabled Optimisation and Design Search for Engineering (G EODISE ) Southampton, Oxford and Manchester Simon Cox- Grid/ W3C Technologies and High Performance Computing Global Grid Forum Apps Working Group Andy Keane- Director of Rolls Royce/ BAE Systems University Technology Partnership in Design Search and Optimisation Mike Giles- Director of Rolls Royce University Technology Centre for Computational Fluid Dynamics Carole Goble- Ontologies and DARPA Agent Markup Language (DAML) / Ontology Inference Language (OIL) Nigel Shadbolt- Director of Advanced Knowledge Technologies (AKT) IRC BAE SYSTEMS- Engineering Rolls-Royce- Engineering Fluent- Computational Fluid Dynamics Microsoft- Software/ Web Services Intel- Hardware Compusys- Systems Integration Epistemics- Knowledge Technologies Condor- Grid Middleware

© Geodise Project, 2001-2004. http://www.geodise.org/ The GEODISE Team... Richard Boardman Sergio Campobasso Liming Chen Mike Chrystall Trevor Cooper-Chadwick Simon Cox Mihai Duta Clive Emberey Hakki Eres Matt Fairman Mike Giles Carole Goble Ian Hartney Tracey Hunt Zhuoan Jiao Andy Keane Marc Molinari Graeme Pound Colin Puleston Nicola Reader Angus Roberts Mark Scott Nigel Shadbolt Wenbin Song Paul Smart Barry Tao Jasmin Wason Fenglian Xu Gang “Luke” Xue

© Geodise Project, 2001-2004. http://www.geodise.org/ Geodise will provide grid-based seamless access to an intelligent knowledge repository, a state-of-the-art collection of optimisation and search tools, industrial strength analysis codes, and distributed computing & data resources G EODISE

© Geodise Project, 2001-2004. http://www.geodise.org/ Example Script hostname = 'pacifica.iridis.soton.ac.uk' jobmanager = [hostname,'/jobmanager-fork'] rsl = '&(executable="/bin/date")(stdout="remote.txt")' %Create a proxy certificate gd_createproxy %Submitting a globus job and returning handle handle = gd_jobsubmit(rsl,jobmanager) %Polling the job gd_jobpoll(handle) %Getting the standard output gd_getfile(hostname,'remote.txt','local.txt'); %Print the output to screen type('local.txt')

© Geodise Project, 2001-2004. http://www.geodise.org/ Aerodynamic Shape Optimisation using CFD  Integration of CAD, mesh generation, and solver  Direct API access to CAD models  third-party standards based data exchange  Robust mesh generation  Automatic mesh generation  Control over mesh properties  Multi-fidelity models  Euler solver  Navier Stokes solver

© Geodise Project, 2001-2004. http://www.geodise.org/ Orthogonal Basis Function for Airfoil Design Robinson, G.M. and Keane, A.J., “Concise Orthogonal Representation of Supercritical Airfoils”, Journal of Aircraft 38(3) (2001) 580-583.  Parameterisation methods for airfoil:  mathematical functions  empirical basis functions  control points based curve fitting  Orthogonal basis functions  unique mapping from parameter space to design space  for preliminary wing design  fewer number of design variables  different set of basis functions for different design task

© Geodise Project, 2001-2004. http://www.geodise.org/ Optimisation Workflow and Results  Optimisation strategy:  Single optimisation method proved to be inefficient for practical problems, more complex strategies are required  Two-stage hybrid approach (Genetic algorithm + Gradient search)  Surrogate modelling  CFD runs on complex configurations is too expensive (24hrs/run)  Surrogate modelling methods  Polynomial curve fitting  Stochastic method (DACE or Kriging)  Neural network  High-dimensional design space  Combing response surface modelling (RSM) /two-stage approach

© Geodise Project, 2001-2004. http://www.geodise.org/ Problem definition Design of Experiment Response surface modelling Optimisation on Response surface Validation ProEngineer CAD (Condor Pool) Gambit Meshing (Globus Compute) Fluent CFD (Globus Compute) Workflow for aerodynamic shape optimisation using CAD, Gambit, and Fluent

© Geodise Project, 2001-2004. http://www.geodise.org/ Response surface model and two-stage hybrid search using GA/Local tuning  Response surface model  two-stage hybrid search methods  Comparison of Airfoil shape and pressure distribution

© Geodise Project, 2001-2004. http://www.geodise.org/ Engine Nacelle Optimisation (problem definition) Negative Scarf Inlet Conventional Inlet 0 12 Total Pressure Recovery (TPR) = Assumption: Noise radiated to ground reduces with increasing scarf angle Objective function: Total Pressure Recovery (pt 2 /pt 1 ) Design variables:Scarf Angle (degrees) Axial Offset (mm) `

© Geodise Project, 2001-2004. http://www.geodise.org/ RSM Construct RSM Evaluate Search Using RSM Best Design Adequate ? RSM Tuning Build Data- Base CFD DoE Initial Geometry CFD … … … … Cluster Parallel Analysis Design of Experiment & Response Surface Modelling

© Geodise Project, 2001-2004. http://www.geodise.org/ Defining the Objective Function CAD geometry Meshing CFD analysis Post-processing Design Variables x 1 = 0.5, x 2 = 0.25 Objective function y = 42 “Bigger workflows are made from little workflows, Little workflows are made from littler workflows, And so on…”

© Geodise Project, 2001-2004. http://www.geodise.org/ Engine Nacelle Optimisation (3D) (some results)  Typical unstructured mesh used in the problem (left)  Response surface model built for two design variables (right)  The effect of other geometry parameters need to be investigated

© Geodise Project, 2001-2004. http://www.geodise.org/ Photonic Device Modelling Bridge waveguide structure courtesy of Martin Charlton, Southampton Microelectronics Research Group. UNIT-CELL PERIODICALLY TILED UNIT-CELLS REAL-THING (photo) pitch=300nm

© Geodise Project, 2001-2004. http://www.geodise.org/ 12-fold Symmetric Quasicrystals F Based on tiling of dodecagons composed of squares and equilateral triangles F Possesses 12 fold rotational symmetry F Leads to a highly homogeneous band gap

© Geodise Project, 2001-2004. http://www.geodise.org/ CEM Simulation Results Photonic Crystal Response Surface / Photonic Band Gap Map CompResource.1 CompResource.2 CompResource.3 CompResource.4 CompResource.1 … 50 frequencies 50 radii

© Geodise Project, 2001-2004. http://www.geodise.org/ Photonic Crystal - Optimisation CAD Model & Parameters Discretization Numerical Solver Intermediate Result Optimised Design Log File CAD Model & Parameters Location, size & density of holes determine the optical bandgap. User “On the Grid” User User: Molinari CAD Model A Parameter1 Rad Parameter2 Pos Optimise BGap Computed X Iter The aim of this design optimisation process is to find a configuration which maximises this bandgap and minimizes energy loss. Energy Bandgap

The Script geometry_optimise_EDIT.m

© Geodise Project, 2001-2004. http://www.geodise.org/ Grid-Enabled Scripting Environment Motivations: v Flexible, transparent access to computational resources v Easy to use for engineers (and in widespread use) Our Approach v Matlab chosen as the hosting environment u Extend the user’s existing PSE u High-level functionality u Quick application development u … is our execution/ enactment engine too v Computational resources exposed in the form of Matlab functions u Job submission to Globus server using Java Cog u Job submission to Condor pool via Web services interface v Integration of CAD, Mesh generation, and Fluent solver via the use of intermediate data format, often standard-based, or package-neutral v Hybrid search strategies to make the best use of different search methods Can also use Python, Jython, etc. Matlab

© Geodise Project, 2001-2004. http://www.geodise.org/ Integration & Scripting Building Blocks Knowledge Services Matlab (or Jython …) Java / C# Web Service Grid Service Java / C#/.NET.EXE/ Fortran/ Matlab Code Intelligent Support Interface Geodise Architecture

© Geodise Project, 2001-2004. http://www.geodise.org/ Grid-Enabled Toolkits in Matlab Function NameDescriptions gd_createproxy Creates a Globus proxy certificate from the user’s credentials gd_proxyinfo Returns information about the user’s proxy certificate gd_proxyquery Queries whether a valid proxy certificate exists gd_certinfo Returns information about the user’s certificate gd_destroyproxy Destroys the local copy of the user’s Globus proxy certificate gd_jobkill Terminates the GRAM job specified by a job handle gd_jobstatus Returns the status of the GRAM job specified a job handle gd_jobpoll Queries the status of a Globus GRAM job until complete gd_jobsubmit Submits a GRAM job to a Globus server gd_getfile Retrieves a file from a remote host using GridFTP gd_putfile Transfers a file to a remote host using GridFTP gd_archive Stores a file in repository with associated metadata gd_query Retrieves metadata about a file based on certain criteria gd_retrieve Retrieves a file from the repository to the local machine gd_sendtext Sends a SMS text message to the specified mobile phone number Proxy management Job submission Data archive Pound, G.E., Eres, M.H., Wason, J.L., Jiao, Z., Cox, S.J., and Keane, A. J., “A Grid –enabled Problem Solving Environment (PSE) for Design Optimisation within Matlab”, 17 th International Parallel and Distributed Processing Symposium (IPDPS 2003) 22-26 April 2003, Nice, France, 2003

Workflow

Workflow Editor DB … Output file Submit to Matlab

Sharing (i) Here's the matlab script you asked for. The script is called sim_pqc.m 'help sim_pqc' will tell you how to use it, I hope the instructions are clear enough. It requires lattice.m and limit.m in your matlab path to run. The density of states will is saved in DOS.mat. everything must be in the same directory. I also included the FDTD and related programs (I had to modify some of them to run in batch mode). Any questions email or phone me at Meso.

Sharing (ii) Simon, Sorry, I found a small mistake in sim_pqc.m Here's the new one Cheers tom P.S. “Provenance” too

Semantics & Knowledge

Semantic Grid in e-Science Bridging the gap: –Grid: seamless access to distributed computation and data resources –e-Science: distributed collaboration and reuse of knowledge and resources –Semantic Grid: Semantic Web technology applied on Grid application Building ontology and semantically enrich resource for reuse and management –Resource is semantically meaningful –Expressed using a standard conceptualization –Which is well recognized within a specific community of practice.

Knowledge Technologies Advanced Knowledge Technologies, IRC (Soton)

Knowledge Acquisition (KA) Knowledge sources Domain experts, software manuals & textbooks. KA techniques Interview, protocol analysis, concept sorting etc. Tools used PC-PACK integrated knowledge engineering toolkit Knowledge acquired EDSO domain knowledge, EDSO processes and problem definition Concept markup in Protocol Editor Concept hierarchy in Laddering Tool

Knowledge Modelling Techniques CommonKADS knowledge engineering methodologies. Knowledge models Organization, agent & task templates, domain schema & inference rules. Tools used PC-PACK integrated knowledge engineering toolkit Deliverables Knowledge web in HTML, XML and UML, Conceptual task model, EDSO process flowchart

Ontologies - common conceptualisation of a domain -

Semantic Workflow support in Geodise Ontology modelling –Definition: Domain conceptualisation that collect a controlled set of vocabulary and their relationship through hierarchy and explicitly expressed properties. –Examples: User profile ontology, Problem profile ontology, Task ontology, etc. Instance generation –Definition: Semantic enriching instances by referencing to ontology files –Methods: annotation content with ontology, populating ontology with content Semantic consumption –Ontology driven instance querying –Ontology driven from generation  task configuration  Problem setup –Ontology assisted domain script editing –Service oriented workflow composing – querying semantic enriched service component.

Ontology Development (1) Tools –Protégé & OilEd Editor Representation –DAML+OIL & CLIPS Deliverables –EDSO domain ontology –EDSO task ontology –Mesh generation tool (Gambit software) ontology –User-profile ontology Protégé Editor OilEd Editor DAML+OIL

Ontology Development (2) Ontology Views –DL ontologies (DAML/OWL) –Simplified views –Tailored to specific domains Ontology Views –Underlying complexity hidden Ontology editing by… – Knowledge engineers – Domain experts Other Views Other Views?? Ontology Client Ontology Server WEB Semantic Network View (Configurable) DAML+OIL/OWL Ontology Instance Store (Database) Geodise Tasks Geodise Concepts FaCT Reasoner GONG Concepts Concept Query View

Ontology Services Facilitating ontology sharing & reuse –Ontology service APIs Domain independence –DAML+OIL/OWL standards Soap-based web services -WSDL Java, Apache Tomcat & Axis technologies

Ontology Assisted Domain Script Editor Pre-defined command syntax ontology with Gambit command syntax instances Semantic rich instances being consumed in the editor Syntax colorizing and auto- completion

Ontology Driven Forms in Geodise -1 Setting up problems (a scenario using JaxFront)

Ontology Driven Forms in Geodise -2 Configuring tasks in Workflow Composing Environment

Exploiting Knowledge in Geodise

Knowledge Application 1: Create Semantic Content Goals –Machine understandable information –Facilitate sharing & reuse Techniques & tools –OntMat- annotizer –Geodise Ontologies Example –OPTIONS log- files annotation

Knowledge Application 2: Ontology-assisted Workflow Management Features: –Function selection –Function instantiation –Database schema –Semantic instances –Semantic workflow Technologies: –EDSO ontologies & ontology services –Java JAX-RPC, DOM/SAX

Knowledge Application 3: Knowledge-based Design Advisor Features –Context-sensitive advice –Advice at multi-levels of granularity (process, task …) –KBSs as knowledge services Technologies –Knowledge engineering –EDSO ontologies –Rule-based reasoning techniques

Intelligent Workflow Monitoring and Advice (“rule-based to case-based in real-time”) Updating constructed workflow using rule-base –At run-time:  find ‘similar’ workflows to the one constructed  is this one performing ‘as expected’? Might a different workflow outperform current one? –Resolution: Perhaps problem is anomalous?  Change method/ modify workflow?  Feedback to expert … update rule-base? Exploiting new components in workflows –Example  New optimisation method added in semantically consistent way  Workflows constructed (by expert) with new method, … and then: –‘similar workflow’ search above will find workflows with new method in:  Might they outperform the currently constructed workflow?  Substitute new method into constructed workflow?  Feedback to expert … update rule-base?

© Geodise Project, 2001-2004. http://www.geodise.org/ A few of my favourite things to do with workflows- review (ii) Create Retrieve Cut ‘n’ Shut Configure Execute Monitor Share Steer Dynamically modify

Questions

© Geodise Project, 2001-2004. http://www.geodise.org/ Example Script hostname = 'pacifica.iridis.soton.ac.uk' jobmanager = [hostname,'/jobmanager-fork'] rsl = '&(executable="/bin/date")(stdout="remote.txt")' %Create a proxy certificate gd_createproxy %Submitting a globus job and returning handle handle = gd_jobsubmit(rsl,jobmanager) %Polling the job gd_jobpoll(handle) %Getting the standard output gd_getfile(hostname,'remote.txt','local.txt'); %Print the output to screen type('local.txt')

Applied Workflows in Geodise e-Science Workflow Services Workshop Edinburgh (Dec 3 rd – 5 th 2003) Dec 4 th 2003 Prof Simon Cox Computational Engineering.

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Applied Workflows in Geodise e-Science Workflow Services Workshop Edinburgh (Dec 3 rd – 5 th 2003) Dec 4 th 2003 Prof Simon Cox Computational Engineering.

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Presentation on theme: "Applied Workflows in Geodise e-Science Workflow Services Workshop Edinburgh (Dec 3 rd – 5 th 2003) Dec 4 th 2003 Prof Simon Cox Computational Engineering."— Presentation transcript:

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